This relates generally to authentication and healthcare, and more specifically, but not by way of limitation, biometric user recognition.
Electrocardiography (ECG, or EKG) is a transthoracic interpretation of the electrical activity of the heart over time captured and externally recorded by, for example, electrodes in apposition with the skin. In ECG biometrics, as with other biometrics, there exists an inherent trade-off between quality of user experience (usability), as reflected in the false reject rate or false non-match rate (FRR or FnMR), and data separability (security), as reflected in the false accept rate or false cross match rate (FAR or FCMR). Receiver-Operator-Curves (ROCs) provide means to quantify such trade-offs, with different biometric technologies having their own characteristic ROCs. Some ROCs are biased toward providing high security at the expense of decreased usability, while others offer superior usability in exchange for lower security.
Fusion biometrics has been introduced to improve overall recognition performance by combining two or more, preferably independent biometric modalities. Fusion biometrics may be implemented, for example, at either the feature extraction level, the matching score level, and/or the decision level. Depending on the target parameter to be optimized, such as FAR or FRR, different fusion methods may be implemented. Some fusion methods necessitate full cross-modality recognition which lowers the FAR but may increase the FRR. Other fusion methods define just one modality sufficient to provide positive recognition which results in a decreased FRR but possibly increased FAR. Fusion schemes may become very complicated with many intermediate possibilities.